Speech or voice technology, in the form of speech recognition, is used in a variety of different environments to facilitate the completion of work or various tasks. One example of a specific use for a voice-directed system is the direction of a worker to perform various tasks and to collect data associated with the task execution.
In a typical voice-directed work system, the worker wears a mobile computer having voice or speech capabilities. The computer is worn on the body of a user, such as at their waist, and a headset device connects to the mobile computer, such as with a cable or possibly in a wireless fashion. In another embodiment, the mobile computer might be implemented directly in the headset. The headset includes one or more speakers for playing voice instructions and other audio that are generated or synthesized by the mobile computer to direct the work of the user and to confirm the spoken words of the user. The headset also has a microphone for capturing the speech of the user to determine the commands spoken by the user and to allow the entry of data using the user's speech and speech recognition. Through the headset and speech recognition and text-to-speech capabilities of the mobile computer, workers are able to receive voice instructions or questions about their tasks, to receive information about their tasks, to ask and answer questions, to report the progress of their tasks, and to report various working conditions, for example.
The mobile computers provide a significant efficiency in the performance of a user's tasks. Specifically, using such mobile computers, the work is done virtually hands-free without equipment to juggle or paperwork to carry around. The mobile and/or wearable computers allow the workers or other users that wear or use them to maintain mobility at a worksite, while providing the users with desirable computing and data-processing functions. Generally, such mobile computers often provide a wireless communication link to a larger, more centralized computer system that directs the work activities of a user within a system and processes any user speech inputs, such as collected data, in order to facilitate the work. An overall integrated system may utilize a central system that runs a variety of programs, such as a program for directing a plurality of mobile computers and their users in their day-to-day tasks. The users perform manual tasks and enter data according to voice instructions and information they receive from the central system, via the mobile computers.
One process is generally referred to as voice-directed work as the user takes specific direction from the central system and their computer like they might take direction from a manager or supervisor or from reading a work order or to-do list. However, voice-directed systems may be overly structured for some users and for some work environments. Various work environments require that the worker know what they are doing in any particular task, and thus they do not have to be told how to specifically perform a particular task or what order to handle multiple tasks. Therefore, voice-assistant systems may be used, such as that system described in U.S. patent application Ser. No. 12/536,696. Voice-assistant systems provide assistance to a worker, as needed or called upon by the worker.
One such environment that requires greater worker flexibility, and is suitable for voice-assisted work is the work environment in a nursing home or assisted living facility. In such facilities, nurses create care plans for all of the residents or patients, and the care plans define the different tasks to be performed by the workers, such as nurses or certified nursing assistants (“CNAs”), for the residents. In particular, each CNA, for example, has to be aware of and accountable for the tasks in the care plans of the residents that are assigned by the nurses to that CNA. The CNA may control the order in which they choose to address a multitude of tasks and thus take advantage of certain efficiencies in their workflow. The workflow will often depend upon the CNAs environment, their location, the urgency of the task and various other factors, and thus they have great flexibility in performing their work.
As part of the work provided within a medical care facility such as a long-term medical care facility, the various caregivers are often required to capture specific information regarding the care that they provide and to document such care. The information and data that is then captured, pursuant to such a documentation task, provides information for other caregivers and entities to utilize in either follow-up care or further processes, such as billing processes.
One type of documented care that is provided to resident in a long-term care environment involves information about the level of assistance that a resident or patient may need in order to complete a particular life activity. Such activities, including eating, bathing, and toileting, for example, are referred to as Activities of Daily Living (ADL). The information that describes the resident performance and level of assistance that is provided in the ADL is referred to as self-performance and support. Currently, self-performance and support information is captured via extremely inefficient or complicated methods in most of the long-term care industry. For example, such self-performance and support information is often captured via time-consuming, face-to-face interviews with care providers. The care providers are then asked to think back over the past several days or weeks so that they might remember the overall level of assistance that they provided for each resident. As such, the prior art processes produce inaccurate information because of the delay between the time when the care is provided, and the time when the face-to-face interviews with caregivers can take place. The accuracy and completion of the self-performance and support information is critical, because such information is a major factor in determining how a long-term care facility is reimbursed through various programs, such as Medicare and Medicaid programs. Accordingly, it is desirable to obtain accurate and current ADL information for a facility to utilize.
Another drawback associated with existing documentation systems for capturing self-performance and support information is that the various levels for a particular ADL activity are difficult to understand. The different levels have subtle nuances that can easily cause a caregiver to give inaccurate information for a particular activity. In a typical system, there are generally give different self-performance levels or gradations that can indicate the type of self-performance of an activity that a resident might accomplish. Each one of the levels has a set of criteria that determines when it should be used to describe the level of assistance that a caregiver might provide during a particular activity. However, the definition of the levels is difficult to understand. Therefore, the criteria are hard to apply in a consistent manner when such definitions are not well understood. Furthermore, in such a system, there are support levels that go hand-in-hand with the self-performance levels. The support levels may include four or more different designated levels. Furthermore, for each self-performance level, there are, at most, two valid support levels that can be used. As such, the entire concept gets complicated very quickly, and may be difficult to understand by the caregiver, particularly if the caregiver is not constantly doing such documentation.
Furthermore, care providers may have a very low education level, and a very low grade reading level. Often, such care providers are not native English speakers, which present a further hurdle with respect to comprehending all the different self-performance and support level definitions, criteria, and combinations for the purpose of capturing accurate and consistent ADL information for the care that they document.
Accordingly, it is desirable to further assist caregivers in the performance of their daily tasks and also in their generation of the data necessary for proper documentation of the care that is provided. Furthermore, it is desirable to address the drawbacks in the prior art, and to provide the ability to capture current and accurate information associated with activities of daily living (ADL) and the various features of same associated with a resident or patient and a care provider.